19 citations · 27 across the 15 of their papers we have counts for
4 papers · 1 filter
Hybrid Pruning: In-Situ Compression of Self-Supervised Speech Models for Speaker Verification and Anti-Spoofing
Junyi Peng, Lin Zhang, Jiangyu Han +5
Although large-scale self-supervised learning (SSL) models like WavLM have achieved state-of-the-art performance in speech processing, their significant size impedes deployment on…
Factors affecting the in-context learning abilities of LLMs for dialogue state tracking
Pradyoth Hegde, Santosh Kesiraju, Jan Švec +5
This study explores the application of in-context learning (ICL) to the dialogue state tracking (DST) problem and investigates the factors that influence its effectiveness. We use…
Approaching Dialogue State Tracking via Aligning Speech Encoders and LLMs
Šimon Sedláček, Bolaji Yusuf, Ján Švec +4
In this work, we approach spoken Dialogue State Tracking (DST) by bridging the representation spaces of speech encoders and LLMs via a small connector module, with a focus on fully…
Analysis of ABC Frontend Audio Systems for the NIST-SRE24
Sara Barahona, Anna Silnova, Ladislav Mošner +14
We present a comprehensive analysis of the embedding extractors (frontends) developed by the ABC team for the audio track of NIST SRE 2024. We follow the two scenarios imposed by N…